Influence of commercial proteases on the proteolysis of enzyme modified cheese : a thesis presented in partial fulfilment of the requirements for the degree of Master of Technology in Food Technology at Massey University, Palmerston North, New Zealand

The influence of four commercial proteases, Protease A, Protease B, Protease C and a two enzyme blend Protease DE, on proteolysis in an enzyme modified cheese (EMC) base has been investigated. Also, a series of preliminary experiments to determine the basic characteristics of the four enzyme preparations in buffer systems has been undertaken. Generally, the exopeptidase activity of the four enzyme preparations was more stable than the endopeptidase activity of the preparations. The highest enzyme activity for all preparations was given at pH 6.5 and Protease B was found to be sensitive to chelating agents. In addition, Protease B was found to contain at least two exopeptidases. Residual protease activities in EMC using a 55% moisture cheese base were found to be 0.005%, 0.009%, 0.007% and 0.004% (w/v) for Protease A, Protease B, Protease C and Protease DE, respectively, following inactivation by heating at 95°C heating for 30 minutes. Under the same incubation conditions (0.15% enzyme at 40°C for 24 h), Protease DE gave greater proteolysis than the three other enzymes and Protease B was the weakest protease. EMC digestion with a combination of proteases was different from that obtained with individual proteases. The combinations of Protease A/Protease C, Protease DE/Protease C, Protease B/Protease C and Protease DE/Protease A showed that the higher the proportion of the former protease in the combinations, the higher the amounts of total amino acids produced in the EMC. The combinations of Protease A/Protease B and Protease B/Protease DE gave greater amounts of total amino acids with the ratio of each enzyme close to 50:50 than with the individual enzymes. With respect to the molecular mass distribution of peptides in the various EMC digestions, Protease DE produced the greatest amount of peptides of 3 or fewer residues and Protease C gave the greatest amount of more medium sized peptides with 11-20 residues. Compared with Protease C, Protease A was more efficient in giving small peptides, while Protease B gave the lowest levels of medium and small peptides, but a high level of free amino acids. In sensory testing, Protease DE produced EMC with a strong pungent and astringent flavour, Protease C gave bitterness, Protease A gave a sweet flavour at a low concentration but bitter flavours with a high concentration and Protease B produced more savoury flavour without bitterness

Hemispheric asymmetry: Looking for a novel signature of the modulation of spatial attention in multisensory processing

The extent to which attention modulates multisensory processing in a top-down fashion is still a subject of debate amongst researchers. Typically, cognitive psychologists interested in this question have manipulated the participants’ attention in terms of single/dual tasking or focal/divided attention between sensory modalities. Here, we suggest an alternative approach, one that builds on the extensive older literature highlighting hemispheric asymmetries in the distribution of spatial attention. Specifically, spatial attention in vision, audition, and touch is typically biased preferentially toward the right hemispace, especially under conditions of high perceptual load. Here, we review the evidence demonstrating such an attentional bias toward the right in extinction patients and healthy adults, and the evidence of such rightward-biased attention in multisensory experimental settings. We then evaluate those studies that have either demonstrated a more pronounced multisensory effect in the right than left hemispace, or else demonstrated similar effects in the two hemispaces. The results suggest that the influence of rightward-biased attention is more likely to be observed when the crossmodal signals interact at the later stages of information processing and under conditions of higher perceptual load – the conditions where attention is perhaps a compulsory enhancer in information processing. We therefore suggest that the spatial asymmetry in attention may provide a useful signature of top-down attentional modulation in multisensory processing

Domain Adaptation for Roasted Coffee Bean Quality Inspection

Current research in machine learning primarily focuses on raw coffee bean quality, hampered by limited labeled datasets for roasted beans. This study proposes a domain adaptation approach to transfer knowledge acquired from raw coffee beans to the task of inspecting roasted beans. The method maps the source and target data, originating from different distributions, into a shared feature space while minimizing distribution discrepancies with domain adversarial training. Experimental results demonstrate that the proposed approach effectively uses annotated raw bean datasets to achieve a high-performance quality inspection system tailored specifically to roasted coffee beans

An average case analysis of a greedy algorithm for the on-line Steiner tree problem

AbstractThis paper gives the average distance analysis for the Euclidean tree constructed by a simple greedy but efficient algorithm of the on-line Steiner tree problem. The algorithm accepts the data one by one following the order of input sequence. When a point arrives, the algorithm adds the shortest edge, between the new point and the points arriving already, to the previously constructed tree to form a new tree. We first show that, given n points uniformly on a unit disk in the plane, the expected Euclidean distance between a point and its jth (1 ≤ j ≤ n − 1) nearest neighbor is less than or equal to (53)√jn when n is large. Based upon this result, we show that the expected length of the tree constructed by the on-line algorithm is not greater than 4.34 times the expected length of the minimum Steiner tree when the number of input points is large